4/22/2026
Optimal Routing for Federated Learning over Dynamic Satellite Networks: Tractable or Not?
Studies optimal routing for federated learning over dynamic satellite networks with relay-based communication between clients and servers.
4/22/2026
Revisiting Catastrophic Forgetting in Continual Knowledge Graph Embedding
Analyzes catastrophic forgetting in continual knowledge graph embedding updates and proposes approaches beyond limiting embedding changes.
4/22/2026
Unsupervised Confidence Calibration for Reasoning LLMs from a Single Generation
Introduces unsupervised method for calibrating confidence estimates in reasoning LLMs using single generation without labels or repeated sampling.
4/22/2026
Heterogeneity-Aware Personalized Federated Learning for Industrial Predictive Analytics
Proposes personalized federated learning approach for industrial predictive analytics accounting for heterogeneous degradation processes across clients.
4/22/2026
EVPO: Explained Variance Policy Optimization for Adaptive Critic Utilization in LLM Post-Training
Proposes EVPO method for LLM post-training via reinforcement learning that optimizes critic utilization in policy gradient optimization.
4/22/2026
When Graph Structure Becomes a Liability: A Critical Re-Evaluation of Graph Neural Networks for Bitcoin Fraud Detection under Temporal Distribution Shift
Evaluates GNN performance on Bitcoin fraud detection under strict inductive protocols, finding random forests outperform GCN, GraphSAGE, and GAT methods.
4/22/2026
Accelerating Optimization and Machine Learning through Decentralization
Reviews decentralized optimization approaches for distributed machine learning across devices with local datasets, emphasizing privacy and scalability benefits.
4/22/2026
Revisiting RaBitQ and TurboQuant: A Symmetric Comparison of Methods, Theory, and Experiments
Comparative analysis of RaBitQ and TurboQuant quantization methods with reproducible experimental framework showing inconsistent performance differences.
4/22/2026
Calibrating Scientific Foundation Models with Inference-Time Stochastic Attention
Proposes stochastic attention modification for transformer-based scientific models to improve calibrated uncertainty estimates at inference time.
4/22/2026
Separating Geometry from Probability in the Analysis of Generalization
Theoretical analysis separating geometry from probability in machine learning generalization bounds for in-sample and out-of-sample performance.
4/22/2026
Structure-guided molecular design with contrastive 3D protein-ligand learning
Framework for structure-based drug discovery combining contrastive 3D protein-ligand learning with autoregressive molecular generation on commercial compounds.
4/22/2026
Lyapunov-Certified Direct Switching Theory for Q-Learning
Theoretical analysis of constant-stepsize Q-learning using stochastic switching systems and Lyapunov methods for convergence certification.
4/22/2026
An Efficient Black-Box Reduction from Online Learning to Multicalibration, and a New Route to $\Phi$-Regret Minimization
Black-box reduction from online learning to multicalibration using no-regret learners and expected variational inequality solvers.
4/22/2026
SAGE: Training-Free Semantic Evidence Composition for Edge-Cloud Inference under Hard Uplink Budgets
SAGE method for edge-cloud hybrid inference under hard uplink bandwidth constraints using semantic evidence composition instead of attention-based importance.
4/22/2026
Disentangling Damage from Operational Variability: A Label-Free Self-Supervised Representation Learning Framework for Output-Only Structural Damage Identification
Self-supervised representation learning framework for structural damage identification that disentangles damage from operational variability without labels.
4/22/2026
HardNet++: Nonlinear Constraint Enforcement in Neural Networks
HardNet++ enforces nonlinear constraints in neural network outputs for control and decision-making with guaranteed constraint satisfaction at inference.
4/22/2026
PREF-XAI: Preference-Based Personalized Rule Explanations of Black-Box Machine Learning Models
PREF-XAI framework generates personalized rule-based explanations for black-box ML models based on user preferences and cognitive constraints.
4/22/2026
Adaptive MSD-Splitting: Enhancing C4.5 and Random Forests for Skewed Continuous Attributes
Adaptive MSD-Splitting algorithm improves discretization of continuous attributes in decision trees like C4.5 and Random Forests for efficiency and accuracy.
4/22/2026
Benign Overfitting in Adversarial Training for Vision Transformers
Theoretical analysis of adversarial training in Vision Transformers, studying robustness to adversarial examples and benign overfitting.
4/22/2026
FB-NLL: A Feature-Based Approach to Tackle Noisy Labels in Personalized Federated Learning
FB-NLL: Feature-based approach handling noisy labels in personalized federated learning with heterogeneous data.
4/22/2026
FASTER: Value-Guided Sampling for Fast RL
FASTER: Value-guided sampling method reducing computational cost of test-time scaling in diffusion-based RL policies.
4/22/2026
Safe Continual Reinforcement Learning in Non-stationary Environments
Safe continual RL for non-stationary environments ensuring constraint satisfaction during learning in physical control systems.
4/22/2026
Scaling Test-Time Compute for Agentic Coding
Method for scaling test-time compute in agentic coding systems using trajectory ranking and value estimates for long-horizon tasks.
4/22/2026
Dual Triangle Attention: Effective Bidirectional Attention Without Positional Embeddings
Dual Triangle Attention: Bidirectional transformer attention mechanism eliminating need for positional embeddings.
4/22/2026
Agent-GWO: Collaborative Agents for Dynamic Prompt Optimization in Large Language Models
Agent-GWO: Multi-agent collaborative system for dynamic prompt optimization in LLMs using genetic wolf optimizer.
4/22/2026
Beyond Indistinguishability: Measuring Extraction Risk in LLM APIs
Analysis showing indistinguishability properties don't prevent data extraction from LLM APIs; formalizes privacy game separation.
4/22/2026
An Empirical Study of Multi-Generation Sampling for Jailbreak Detection in Large Language Models
Empirical study of jailbreak detection in LLMs using multi-generation sampling on JailbreakBench with varying model alignment.
4/22/2026
ARES: Adaptive Red-Teaming and End-to-End Repair of Policy-Reward System
ARES: Red-teaming and repair method for RLHF systems addressing vulnerabilities in both policy and reward model simultaneously.
4/22/2026
AI scientists produce results without reasoning scientifically
Evaluation of LLM-based scientific agents across 8 domains with 25k runs assessing whether they follow scientific reasoning norms.
4/22/2026
Semantic Needles in Document Haystacks: Sensitivity Testing of LLM-as-a-Judge Similarity Scoring
Framework testing LLM sensitivity to semantic changes in document comparison tasks using perturbation-based needle-in-haystack experiments.
4/22/2026
Hierarchically Robust Zero-shot Vision-language Models
Hierarchically robust zero-shot vision-language models defending against adversarial attacks on both base and superclass levels.
4/22/2026
Less Is More: Cognitive Load and the Single-Prompt Ceiling in LLM Mathematical Reasoning
Empirical study of prompt engineering for formal mathematical reasoning, analyzing 40+ prompt variants in equational theory competition.
4/22/2026
MORPHOGEN: A Multilingual Benchmark for Evaluating Gender-Aware Morphological Generation
MORPHOGEN: multilingual benchmark for evaluating LLM handling of gender-aware morphological generation in 13 languages.
4/22/2026
Personalized Benchmarking: Evaluating LLMs by Individual Preferences
Framework for personalized LLM benchmarking that evaluates alignment with individual user preferences instead of aggregate ratings.
4/22/2026
$R^2$-dLLM: Accelerating Diffusion Large Language Models via Spatio-Temporal Redundancy Reduction
R²-dLLM: acceleration technique for diffusion-based LLMs via spatio-temporal redundancy reduction during parallel token decoding.
4/22/2026
TRN-R1-Zero: Text-rich Network Reasoning via LLMs with Reinforcement Learning Only
TRN-R1-Zero: zero-shot reasoning on text-rich networks using LLMs with reinforcement learning, integrating textual semantics with graph structure.
4/22/2026
SAHM: A Benchmark for Arabic Financial and Shari'ah-Compliant Reasoning
SAHM: benchmark and instruction-tuning dataset for Arabic financial NLP and Sharia-compliant reasoning with 14,380 examples.
4/22/2026
Design Rules for Extreme-Edge Scientific Computing on AI Engines
Design principles for deploying machine learning models on extreme-edge AI hardware with latency/throughput constraints using spatial dataflow.
4/22/2026
Auditing LLMs for Algorithmic Fairness in Casenote-Augmented Tabular Prediction
Audits fairness properties of LLM-based tabular classification on housing placement prediction with real nonprofit casenote data, evaluating multi-class classification error disparities.
4/22/2026
Sherpa.ai Privacy-Preserving Multi-Party Entity Alignment without Intersection Disclosure for Noisy Identifiers
Privacy-preserving entity alignment method for vertical federated learning without disclosing intersection information using noisy identifiers.
4/22/2026
Beyond Semantic Similarity: A Component-Wise Evaluation Framework for Medical Question Answering Systems with Health Equity Implications
Evaluation framework for medical question answering systems using LLMs, assessing accuracy and health equity implications beyond semantic similarity.
4/22/2026
Evaluating LLM-Generated Obfuscated XSS Payloads for Machine Learning-Based Detection
Evaluation of LLM-generated obfuscated XSS payloads and their detection by machine learning-based security systems.
4/22/2026
Detecting Hallucinations in SpeechLLMs at Inference Time Using Attention Maps
Method for detecting hallucinations in speech-based LLMs using attention map metrics without requiring gold-standard outputs.
4/22/2026
Chat2Workflow: A Benchmark for Generating Executable Visual Workflows with Natural Language
Benchmark dataset and methods for generating executable visual workflows from natural language descriptions using AI.
4/22/2026
Learning Hybrid-Control Policies for High-Precision In-Contact Manipulation Under Uncertainty
Reinforcement learning approach to learn hybrid control policies for high-precision robot manipulation tasks with force constraints.
4/22/2026
VLA Foundry: A Unified Framework for Training Vision-Language-Action Models
Open-source unified framework for training vision-language-action models with shared training stack from language pretraining to action fine-tuning.
4/22/2026
Generative Models and Connected and Automated Vehicles: A Survey in Exploring the Intersection of Transportation and AI
Survey examining generative models applied to connected and automated vehicles for simulation, prediction, and decision-making in autonomous driving.
4/22/2026
Resource-aware Mixed-precision Quantization for Enhancing Deployability of Transformers for Time-series Forecasting on Embedded FPGAs
Mixed-precision quantization technique for deploying transformer models on resource-constrained embedded FPGAs for time-series forecasting.
4/22/2026
AutoNFS: Automatic Neural Feature Selection
AutoNFS: Automatic neural feature selection method for high-dimensional tabular data that detects optimal feature count without retraining.
4/22/2026
RESFL: An Uncertainty-Aware Framework for Responsible Federated Learning by Balancing Privacy, Fairness and Utility
RESFL: Framework balancing privacy, fairness and utility in federated learning using uncertainty-aware differential privacy techniques.